Division of Physiological Chemistry II, Karolinska Institutet, Stockholm.
Eur Respir J. 2013 Sep;42(3):802-25. doi: 10.1183/09031936.00078812. Epub 2013 Feb 8.
Inflammatory lung diseases are highly complex in respect of pathogenesis and relationships between inflammation, clinical disease and response to treatment. Sophisticated large-scale analytical methods to quantify gene expression (transcriptomics), proteins (proteomics), lipids (lipidomics) and metabolites (metabolomics) in the lungs, blood and urine are now available to identify biomarkers that define disease in terms of combined clinical, physiological and patho-biological abnormalities. The aspiration is that these approaches will improve diagnosis, i.e. define pathological phenotypes, and facilitate the monitoring of disease and therapy, and also, unravel underlying molecular pathways. Biomarker studies can either select predefined biomarker(s) measured by specific methods or apply an "unbiased" approach involving detection platforms that are indiscriminate in focus. This article reviews the technologies presently available to study biomarkers of lung disease within the 'omics field. The contributions of the individual 'omics analytical platforms to the field of respiratory diseases are summarised, with the goal of providing background on their respective abilities to contribute to systems medicine-based studies of lung disease.
在发病机制以及炎症、临床疾病和治疗反应之间的关系方面，肺部炎症性疾病非常复杂。目前已经有复杂的大规模分析方法可用于定量检测肺部、血液和尿液中的基因表达（转录组学）、蛋白质（蛋白质组学）、脂质（脂质组学）和代谢物（代谢组学），以确定可定义疾病的生物标志物，这些生物标志物涉及联合的临床、生理和病理生物学异常。人们期望这些方法能够改善诊断，即定义病理表型，并有助于监测疾病和治疗，同时还能揭示潜在的分子途径。生物标志物研究可以通过特定方法测量预先定义的生物标志物，也可以应用“无偏”方法，该方法涉及的检测平台对焦点没有选择性。本文综述了目前在“组学”领域研究肺部疾病生物标志物的技术。总结了各个“组学”分析平台对呼吸疾病领域的贡献，目的是提供背景信息，了解它们各自在基于系统医学的肺部疾病研究中做出贡献的能力。
